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Build and optimize distributed training systems for large neural networks (LLMs, diffusion, SSMs) across GPU clusters, focusing on throughput, stability, and fault tolerance using PyTorch, Megatron-LM, and DeepSpeed.
Build AI-powered computer vision systems for drones to navigate without GPS, training neural networks for real-time obstacle detection and terrain recognition on embedded hardware.
Senior ML Engineer at Joom in Lisbon, Portugal, building and optimizing recommendation/search systems and marketing automation using Python, Scala, Spark, Go, and modern LLMs.
Build and optimize a compiler stack for robotics simulation and AI training, using LLVM, JIT, and GPU codegen to maximize performance.
Architect and own the MLOps infrastructure for adaptive AI models in a regulated medical-device setting, defining versioning, validation, and PCCP-style change-control processes.
Analyze data to extract insights, automate workflows, and support decision-making for sales, marketing, and operations using SQL, R, and statistical modeling.
Build and deploy LLM-based applications using frameworks like PyTorch and Hugging Face, focusing on NLP and large language models such as LLaMA.
Build and deploy ML models using TensorFlow and NLP, quantize models for mobile, and analyze large datasets to enhance products.
Build and refine market-making models for equities and derivatives using Python, AWS SageMaker, and deep learning (LSTMs, CNNs) to predict short-term price movements and backtest strategies.
Design and build enterprise-scale graph data platforms using TigerGraph on AKS Kubernetes to power fraud detection, financial crime analytics, and customer intelligence with graph-based ML and real-time analytics.
Design and deploy deep-learning perception models for autonomous systems, focusing on computer vision and edge deployment using frameworks like PyTorch or TensorFlow.
Build and improve core ML components for an AI-native assistant that handles long-running tasks, retains context, and interacts with external tools in production systems.
Build and ship AI features end-to-end, designing prompts, workflows, and systems to turn raw model outputs into reliable product behavior in production.
Lead semiconductor process integration for DRAM/NAND uniformity, using model-based analysis and cross-site collaboration to optimize yield and reliability in memory manufacturing.
Build and scale generative and predictive ML models for cellular behavior using PyTorch and distributed training, bridging research prototypes to production-grade systems in a TechBio company.
Build next-gen generative models of cellular behavior to guide drug discovery, using single-cell multi-omics and ML to predict intervention effects and design experiments.
Principal Data Scientist at Xsolla to architect ML solutions, lead fraud/anomaly detection models, and mentor teams in the video game industry.
Build and evaluate ML models for entity matching using embeddings, LLMs, and NLP on messy, multilingual datasets; design experiments, metrics, and scalable inference pipelines.
Intern designs and implements computer-vision models for embedded systems, optimizing object detection and AI inference on edge devices like NVIDIA Jetson.
Lead Affirm’s ML underwriting systems, designing and scaling advanced models (e.g., Transformers, XGBoost) with PyTorch and Spark to drive transparent credit decisions and mentor senior engineers.
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